ledmirror.py

#!/usr/bin/env python
#
# (C) 2014 Joe Schwartz & Square Design, Inc.
#
# Uses the image from a webcam to control a grid of 32 Neopixel strips with 48
# pixels on each strip.
# 
import signal
import sys
import numpy as np
import math
import cv2 
import opc
import time

print "Starting ledmirror - press CTRL-C to exit"

cap = cv2.VideoCapture(0)

def signalHandler(signal, frame):
	print "Closing camera"
	cap.release()
	sys.exit(0)

signal.signal(signal.SIGINT, signalHandler)

# Initialize the client connection to the local fcserver.
client = opc.Client('localhost:7890')

# For transforming the captured frame to a reduced resolution frame.
# TODO: get camera resolution from API
capCols = 640
capRows = 360
MIRROR_COLS = 32
MIRROR_ROWS = 48

colStep = math.floor(float(capCols) / MIRROR_COLS)
rowStep = math.floor(float(capRows) / MIRROR_ROWS)

while(True):
	# Capture frame-by-frame
	ret, frame = cap.read()

	# Process the frame. For the frame pixel array  [i, j],  i refers to rows and
	# j refers to columns. Use fast splicing to grab a reduced resolution array
	# corresponding to the Neopixel grid.
#	frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
	reducedFrame = cv2.resize(frame, (MIRROR_COLS, MIRROR_ROWS))
	reducedFrame = reducedFrame[:, ::-1]
	reducedFrame = np.roll(reducedFrame, 2, axis=2)


	#print "Frame size: {0}".format(frame.shape)
	#reducedFrame = frame[0::rowStep, 0::colStep]
	#print "Reduced frame: {0}".format(reducedFrame.shape)
	#if reducedFrame.shape[0] > MIRROR_ROWS:
#		reducedFrame = reducedFrame[0:MIRROR_ROWS]
	#print "Re-Reduced frame: {0}".format(reducedFrame.shape)

	# The Neopixel grid is addressed as a 2-dmensional array.
	ledArray = np.reshape(reducedFrame, (reducedFrame.shape[0] * reducedFrame.shape[1], 3), 'F')
	client.put_pixels(ledArray)
	time.sleep(0.1)
#	cv2.imshow('frame', frame) #gray)
#	if cv2.waitKey(1) & 0xFF == ord('q'):
#		break

# When all is done, release the capture
cap.release()
cv2.destroyAllWindows()